Social support moderates the relationship between sleep and inflammation in a population at high risk for developing cardiovascular disease
Bibliographic record
Abstract
Poor sleep and low social support have each been associated with mortality and morbidity from chronic illness, and a small body of research suggests that the two interact to influence systemic inflammation whereby good social relationships may buffer the relationship between poor sleep and increased inflammation. The current study investigated interactions between sleep and social support in the prediction of inflammation in a clinical population (prehypertensive and hypertensive individuals) at high risk for the development of cardiovascular disease. Using a standardized subjective measure of sleep quality, we found that social support moderated the association between sleep and circulating levels of both IL-6 and CRP, such that poor sleep appeared to confer a risk of increased inflammation only in those participants who also reported low social support. In women, the same relationship was observed for TNF-α. These results extend previous findings into a clinical population and also demonstrate that sleep quality and social support interact in the prediction of two previously uninvestigated clinically relevant inflammatory markers (CRP and TNF-α). High levels of perceived social support may compensate for the negative health impact of poor sleep quality and vice versa.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".